Latest / Glovisor Podcast / Her Mom Fell—So She Invented an AI Device to Change Patient Mobility | Sheila Buswell (Ep 60)
Transcript
- Joe Abreu - GLOVISOR: Can thousands of lives change because of the hardest moments you've ever faced? This is a story about resilience, innovation, and purpose. Welcome to the Glovisor Podcast, where we explore business growth, communication, and personal development through real conversations with people that make an impact. Our guest is the CEO and co-founder of Buswell Biomedical, the company behind upward mobility, an AI-enabled mobility device transforming how hospitals support patient movement. A US Army veteran and engineer, she brings a passion for restoring patients' independence, reducing caregiver strain, and pushing healthcare forward through innovation, entrepreneurship, and resilient leadership. Glovisor welcomes Sheila Buswell Sheila Buswell: Thank you, Joe. I'm happy to be here. Joe Abreu - GLOVISOR: Well, pleasure. Looking forward to the conversation. All right. So, Sheila, let's begin. Please share with us a little bit more what will you do. Sheila Buswell: being a patient myself, but mostly when I saw my mom in rehab, I wanted to empower her in a way, and I wanted to empower myself and patients totally. And I'm an engineer, so I look at things technically, and I was like, well, how do we solve this problem? And then every day I try to solve that problem and make it more obtainable for everybody in those situations. And so day to day I work to further the business. And sometimes that's cleaning toilets and taking out trash, but sometimes it's pitching, you know, for millions of dollars or, you know, hundreds of thousands of dollars to venture capitalists or angel investors. Joe Abreu - GLOVISOR: tell us a little bit more about Buswell Biomedical. What are you focusing on right now? Sheila Buswell: We have the product Upwork Mobility Upmo for short. and it we got I got a patent for it where the whole business is formed around that and to get input from healthcare workers to make them safer and from people who are patients or have loved ones that were patients and see what what we could add. And one we problem that we hear all the time is that when you're in a hospital or rehab setting, activities of daily living, especially toileting, can be cumbersome. And so to figure out how to do that. and make it expeditious and because when you have to go, you have to go. You can't wait hours sometimes. And that would be that's a meaningful work, But when I worked for a beer company, I didn't, you know, it wasn't that meaningful. When I worked for Harley Davidson, not that meaningful. But this is meaningful on a level I can't explain. Like to make people's lives better. Joe Abreu - GLOVISOR: Yeah, that makes sense. Now, does the patient have the ability to move out of the bed using the upward mobility on their own, or does a caregiver or a nurse have to help the patient? Sheila Buswell: the answer to that would be it would depend on the patient. The idea is to empower people where they can. And so right, the current status of care is if you have to conduct any activity of daily living and you're considered a mobility concern, you call a nurse or a healthcare worker. the Healthcare worker comes or an entourage of healthcare workers when they can do the things. When you can I mean, you're supposed to lift like 50 pounds. And I haven't weighed 50 pounds since I was under five. But like you need to have a number of people. Even my mom was 99 pounds. She had to have two people in theory. But you would call this device Epo. And it would travel to you autonomously like a self-driving car. They have wheelchairs that do this in airports, but I don't think that's the best using lighter technology like a Roomba or a self-driving car to come to you in an airport or in a hospital setting. And then if you're able to, this device, you'd hook your own the lanyard to your specialized harness, and then you put that harness on like a jacket, and then you could go conduct any activity day living by yourself. If you're able to do that, if you're not, it could help people in a situation if a healthcare worker needs to come, because it turns one healthcare worker into many, because they won't have the same strain. Like they're using more cognitive ability, hand-eye coordination, not brute strength lifting, Joe Abreu - GLOVISOR: this is really interesting. So I guess just for more clarification, just because I haven't seen this in in progress, but so if you're in a room in the hospital, you can call this device that will self-drive to your room. And then if I'm able to, as a patient, I can just latch on and it will help me get out of bed. Will will it bring me to the restroom or will it just help me up? Sheila Buswell: the reason you have a specialized harness is it can it knows your body. Like I walk with a limp and it knows that that would be normal for me, but it probably isn't normal for most people. But it would compare what everybody's motion is, and that's the machine learning part, with your motion, and anticipate a fall and produ but other than s the way it would prevent a fall is like a little kid when you when it's learning how to walk, you pick it up. And it's not to have somebody a patient hanging there like a pinata. It's just so that you can have your f feet under you like and stabilize yourself. But you go to the bathroom, any if you're most people fall between 11 p.m. and 1 a.m. Go into the bathroom. So the idea is to and when healthcare workers are going to help somebody, There it's usually he had to go like when you rang the button, when you rang for help, right? Like you're not sometimes they wait for hours. when you go into a rehab facility, you meet with a person who's like a RN or equivalent and they can assess whether you're physically able And that the assessment needs to be made at that level. And at that time, they would also say, you know, if you have if you stumble, you can control lower to the ground. They could pick the re the corrective action or raise you up a little bit so that you could get your feet under you, take your weight off. Off weight people, I think is the right term. And right now, the this type of device is used in the Hakoma. It's around to fit around a treadmill in physical therapy. But the upward mobility would fit through a doorframe and around a toilet. So that's why it's used in hospitals and rehabilitation hospitals because the door frames are standardized. In houses, they're not, you know. But I think once we get that motion library, we can find out where people are unstable. And we know a lot of people have stabilization issues in the bathroom. Right. Like there's a but there's a lot going on there. There's standing up. If it's particularly you have a problem standing up or sitting down or walking is a there's a huge library on that. But people who the ultimate goal is to let people stay in their houses longer. But we can learn a lot from the motion of when people fall the most and what predictors are identify you as soon to fall we want to stop that or limit it that travel distance to six inches or you know to not get to the point where in hospitals they say an unplanned descent to the floor with and without injury. That's a whole thing. But the idea that we would just be able to make people safer and pe patients safer and healthcare workers safer because your healthcare workers get injured a lot of the time helping heavier patients or helping patients, period. You're not there's the OSHA thing of lift with your legs, not your back. Well, what do you catch with in an emergency? Whatever, Joe Abreu - GLOVISOR: Now, how does AI integrate with the hospital? you mentioned how different patients will have different requirements. is there an integration where it identifies which patient can do which task? Sheila Buswell: I think most people when they think of artificial intelligence, they think of large language models like my Chat GPT can write an email for me or Grock can tell me what the best pet sitters or pet trainers are. And I think the idea of a machine learning and that's where it goes to. It's like the understanding of motion and ha like what's normal motion and what's right now we don't know enough about what predicts a fall. Some people just fall, but there are some things that, you know, they know. little rugs all over your house can make people trip and fall. So eliminating that and little things we can learn where we help we're gonna have more data we can get more information from it. So that's how it integrates. The machine learning algorithm that determines stability. And then the self-driving car, I use that like the upmode driving to you. like a Roomba or a self-driving car, it totally is a LIDAR technology that's artificial intelligence. It know it can determine if there's obstructions that they need to avoid. Different hospitals have different states have different laws. Like I think Texas had a hospital shooting or something. And so there is doors that have to remain shut. And there's limited ability f to travel from one place to another. So that would have to be navigated and have to use artificial intelligence, Joe Abreu - GLOVISOR: every successful entrepreneur has that defining moment that made them make that item or or or come up with that idea and put it to action. What inspired you to pursue this path? Sheila Buswell: It definitely I didn't have the entrepreneurial ship spirit. It was one of those things where I l I gave myself a pep talk. If not you, then who and if not now then when. And so we talked before. I got it I had a scholarship when I graduated high school to the University of Utah. It was tied to a high GPA that I did not maintain. And after two years I joined the US Army. And I was injured in Bosnia in nineteen ninety eight on a deployment there. And I had a generator fell off a forklift and hit. my foot was under it. And I was a patient in a UN hospital called the Blue Factory. I'm sure they call all the knowing the military, that's what it's called. On a peacekeeping mission or any anyway. It was a thing where I was like I had a cadre of Norwegian nurses and I had no problem there. But it was like I that was the hardest thing for me to get. Not there wasn't a shortage of people. It was just that, man, going to the bathroom when there's somebody there is just not something you want to do. And after I got out of the military, I got a medical discharge and I got out in 2001. And then 20 years later, my mom Falls in Arizona and has an accident. But this time, after those 20 years, I worked for a lot of great companies. I ultimately obtained a master's in engineering, right? So I go out to, I'm not a caregiver. So I go out there and my first impulse. is to be mean to the healthcare workers. Because my mom's I was frustrated. And I saw my mom struggle with the same standard of care that I had experienced twenty years prior. And I knew by this time that there was a better way. But it's hard when you're talking to healthcare workers, they think large language model, I'm this is means more paperwork. And I don't want more paperwork. I wanna I they don't mind helping people go to the bathroom. That's something they can do. They're trained for that. They're expecting that. Filling out a paperwork to keep the lawyers happy is not what they want to do. But I was able to identify a solution to the problem. And I thought at the time I'll just go work for the company that's developing a solution to this. Well, that problem was there nobody was developing the solution. Like, so I was like, well, I I figured out how to solve the problem and I was like, well, what to do now? And so I started Buswell Biomedical and obtained a patent for the Upmo, Joe Abreu - GLOVISOR: So can you share with us a little bit about how long did that process take? From the moment that you realized there was a need, you found that no one was fulfilling it, and now you're gonna step up and you you designed this machine, this AI mobility or upmo as you call it and you designed it and then you put in so how long did that process take to get to the point where where you're patent and ready to roll? Sheila Buswell: what happened initially when my mom fell? It was like April of 2019 or 2018. And then I figured out a solution by June, but and I it took a while, I would say a couple months, to determine that there wasn't anybody working on this. And I was just gonna, I have this personal experience, I can go work on it. And and that was 2018 and now it's 2026, and then closed in that time frame it was first I wanted to prove that my idea was feasible right so I went and d developed a short machine learning library and I got a hundred specimens with four inertial measurement units and I gave it to a data scientist. But it was awesome because the time was like twenty twenty and I was going around and be like, all the age group, male and female across the age spectrum. It was really great to talk to a twenty year old man as a mid middle aged woman and be like, stand up and sit down for science. I need to capture your emotion It was weird. There was no way to that took a lot of the military in me to be like, We're gonna do this and it's what for bet It's for the betterment of humanity. But it was hard. And then to get that proven and then to prove that it was feasible. And then we got a mechanical prototype and tested that it could we physically made it so it could fit through a doorframe and around a toilet, but then it was like stable enough and it could lift enough weight. So we have a mechanical prototype that can lift 500 pounds at a reasonable speed, Timing is part of the heav everything. And like having the idea, I thought we had an idea and it was needed and there was a need for it. But it's almost like you don't realize you have a problem, or people don't realize they're gonna be old and in that it's really hard to sell somebody who's in their 30s that they're gonna be in a nursing home or you're gonna have problems with your knees. And that's a difficult sell, but it's easier. to talk to people about their loved ones. For myself, when I was 20 years old, it was like, yeah, this is terrible. But it was more mentally taxing and pulled at my heartstrings more when I saw my little mama waiting to go, you know, for any of the activities of daily living and to solve those problems. It's something that's going to affect everybody. And it's important to work on like I keep saying, bringing this back to it's it I feel like this work is meaningful and it's going to impact a lot of lives in the future. Joe Abreu - GLOVISOR: you have a prototype. What is the next step after this? Sheila Buswell: Well, we d absolutely need FDA clearance, but to get to FDA clearance, we have to figure out that this is safe and efficable and we have to be able to prove that. And then so there's a lot of testing involved. And I don't Joe, it's really expensive to get testing and to develop a machine learning algorithm, but that's the next steps. Joe Abreu - GLOVISOR: So who should be contacting you right now? Sheila Buswell: So venture capitalists or angel investors would be great. But I'd love to hear from people who ha have been patients, have loved ones or patients, or healthcare workers to just give me your input. What problems we could solve? That would be great. What problems have you faced that you think we could help with? Joe Abreu - GLOVISOR: So that's helpful, right, to listen some feedback and then integrating. And I guess that would be version two, version three. And as you move along, these models just continue improving like every other product that gets to market. Sheila Buswell: Well, and I think when more people we get more people using it, we're gonna get more input. We get more people i am a total believer in that the more people use it, that's feedback you get. You have but you have to ask the right questions, you have to get it. Doing things in a vacuum, I've learned so much, mostly around what I didn't know before. But healthcare workers specifically, they ha they fight those battles daily. So what could we do to help make your life easier? Joe Abreu - GLOVISOR: if one of our listeners is an angel investor and contacts you today and just gives you endless amount of money, how long before you think you can get to market? Sheila Buswell: after we get the FDA clearance, I think it would be about six months. Joe Abreu - GLOVISOR: Yeah, 'cause I can see this model being very interesting to hospitals today, but I think ultimately other variations that may be a little smaller, they can be used in the home. Some people may be interested if it can fit, Sheila Buswell: Well, that's the biggest thing about I think our ultimate goal is when we learn more about motion. But we can't make something any smaller, door frames in h houses are variable. Like our house in the city, when we lived near St. Louis City, it was a hundred year old house and it had one door frame that was twenty eight inches. So there's people these days that are bigger than twenty eight inches across. So it's very hard to make something or if not impossible, structurally sound to prevent a fall and be mobile and but if we know that you're you have these moments of instability when you stand where we could place stuff that doesn't have to move so that you're you can stay in your house longer. Joe Abreu - GLOVISOR: Now, if listeners remember only one thing from today's conversation, what do you hope that message is? Sheila Buswell: I think when I was young, and it would still serve me, it still serves me today, is to just trust my gut more than I do other people. And because you have that's your intuition. And I think that a lot of people think we're only gonna be able to do this or that that and it's not ill-intentioned. It's just they're limited by their experiences and their education. And I think that's what led me down this path of entrepreneurship. And s it's just being open to that and just being like, okay, we are offering something, and people think exoskeleton, people think they're robotics in a different way. Like they think a robot is gonna be like the humanoid robot that can run faster than Hussein Bolt. Well, it might be a robot that folds your laundry or does your dishes, or at Harley Davidson we had packaging robots that were awesome to watch, but they did not look like a humanoid. And I think to Really think outside the box. You need to be well. And to solve problems, you need to be able to trust your gut. Joe Abreu - GLOVISOR: Now, where can our audience connect with you? Find out more about your work and continue this conversation. Sheila Buswell: Busfobiomedical dot com Joe Abreu - GLOVISOR: Nice and easy. Sheila, thank you so much for sp spending time with us today and sharing your story and your invention. I'm looking forward to seeing it in person. Sheila Buswell: Thank you. Thanks, Joe. Joe Abreu - GLOVISOR: Thanks everyone for listening. If this episode inspired you, share it with someone who needs it. And don't forget to follow the Glovisor Podcast for more conversations to make an impact. Till the next time.